ARTICLE OPEN ACCESS

Diagnosing Mitochondrial Disorders RemainsChallenging in the Omics EraPatrick Forny MD PhD Emma Footitt PhD James E Davison PhD Amanda Lam PhD

Cathy E Woodward BSc Spyros Batzios MD PhD Sanjay Bhate MD Anupam Chakrapani MD

Maureen Cleary MD FRCP Paul Gissen PhD Stephanie Grunewald FRCP PhD Jane A Hurst FRCP

Richard Scott PhD Simon Heales PhD Thomas S Jacques FCPath Thomas Cullup FRCPath and

Shamima Rahman FRCP PhD

Neurol Genet 20217e597 doi101212NXG0000000000000597

Correspondence

Dr Rahman

shamimarahmanuclacuk

AbstractObjectiveWe hypothesized that novel investigative pathways are needed to decrease diagnostic odysseysin pediatric mitochondrial disease and sought to determine the utility of clinical exome se-quencing in a large cohort with suspected mitochondrial disease and to explore whether any ofthe traditional indicators of mitochondrial disease predict a confirmed genetic diagnosis

MethodsWe investigated a cohort of 85 pediatric patients using clinical exome sequencing and comparedthe results with the outcome of traditional diagnostic tests including biochemical testing ofroutine parameters (lactate alanine and proline) neuroimaging and muscle biopsy withhistology and respiratory chain enzyme activity studies

ResultsWe established a genetic diagnosis in 365 of the cohort and report 20 novel disease-causingvariants (1 mitochondrial DNA) Counterintuitively routine biochemical markers were morepredictive of mitochondrial disease than more invasive and elaborate muscle studies

ConclusionsWe propose using biochemical markers to support the clinical suspicion of mitochondrialdisease and then apply first-line clinical exome sequencing to identify a definite diagnosisMuscle biopsy studies should only be used in clinically urgent situations or to confirm aninconclusive genetic result

Classification of EvidenceThis is a Class II diagnostic accuracy study showing that the combination of CSF and plasmabiochemical tests plus neuroimaging could predict the presence or absence of exomesequencing confirmed mitochondrial disorders

MORE ONLINE

Class of EvidenceCriteria for ratingtherapeutic and diagnosticstudies

NPuborgcoe

From the Mitochondrial Research Group (PF SR) UCL Great Ormond Street Institute of Child Health Metabolic Medicine Department (PF EF JED S Batzios AC MC PGSG SR) Great Ormond Street Hospital for Children NHS Foundation Trust Neurometabolic Unit (AL SH) National Hospital for Neurology and Neurosurgery Department ofChemical Pathology (AL SH) Great Ormond Street Hospital for Children NHS Foundation Trust Neurogenetics Unit (CEW) National Hospital for Neurology and NeurosurgeryDepartment of Neurology (S Bhate) Department of Clinical Genetics (JAH RS) North East Thames Regional Genetics Service DBC Programme (TSJ) UCL Great Ormond StreetInstitute of Child Health and Department of Histopathology and London North Genomic Laboratory Hub (TC) Great Ormond Street Hospital for Children NHS Foundation TrustUnited Kingdom

Go to NeurologyorgNG for full disclosures Funding information is provided at the end of the article

The Article Processing Charge was funded by CRUK

This is an open access article distributed under the terms of the Creative Commons Attribution License 40 (CC BY) which permits unrestricted use distribution and reproduction in anymedium provided the original work is properly cited

Copyright copy 2021 The Author(s) Published by Wolters Kluwer Health Inc on behalf of the American Academy of Neurology 1

Mitochondrial diseases are multisystemic complex disorderswhich are difficult to diagnose They are caused by pathogenicvariants in at least 350 different genes across 2 genomes1 andthis list continues to grow with the frequent discovery offurther disease genes The challenge of finding a diagnosis forpatients affected by a mitochondrial disorder arises from thevariability in disease presentation regarding symptoms andage at onset2 as well as the lack of consistent biochemicalmarkers3 Many of the clinical symptoms of mitochondrialdisease for example muscular hypotonia and weakness gutdysmotility and neurologic impairment are shared by a widerange of different disease processes and so are not useful toidentify the specific defective gene in a patient4 Similarlyblood biochemical markers such as elevated lactate and ala-nine are helpful to raise the suspicion of a mitochondrialdisorder but are not specific enough to point to a particulargene defect3 Moreover these biomarkers may be normal inindividuals with genetically confirmedmitochondrial disease5

Basic biochemical measurements including plasma lactatealanine and proline are routinely used to assess the proba-bility of the presence of a mitochondrial condition Elevationsof these biomarkers are all due to the reduced mitochondrialutilization of pyruvate6 which can be converted to lactate bylactate dehydrogenase or transaminated to form alanine7

Raised proline is either due to inhibition of proline oxidase bylactate8 or increased proline synthesis from glutamate sec-ondary to perturbed oxidative phosphorylation9 In additionto these biomarkers muscle biopsy is traditionally used to aidthe diagnosis of mitochondrial disease10-12 As muscle is ahigh-energy-requiring organ mitochondrial defects fre-quently manifest in muscle tissue even in the absence of sig-nificant clinical myopathy13 Muscle tissue investigations(respiratory chain enzyme activity [RCEA] analysis andmuscle light and electron microscopy) have limited ability topredict a mitochondrial disorder since they do not displayconsistent abnormalities in all cases Moreover muscle biopsyis invasive and associated with a risk of metabolic de-compensation during general anesthesia particularly in youngchildren with mitochondrial disease Finally secondary RCEAdeficiencies and histologic changes may be observed in severalnonprimary mitochondrial diseases14

To address this lack of diagnostic accuracy the omics erabrought new technologies which are useful in assessing thegenetic cause of a mitochondrial disorder at a wide and high-throughput scale1516 In this study we used next-generationsequencing technology to investigate 85 consecutive patientswith a suspected mitochondrial disorder in a single center by

studying a clinical exome panel of 168 nuclear genes based ona shared gene panel developed by Genomics England17 whichincludes moderate- and high-level evidence genes with regardto their disease association Additional clinical exome panelswith other disease foci were analyzed based on the clinicalpresentation of individual patients The presented study de-scribes the real-world experience of diagnosing mitochondrialdisease using novel sequencing techniques and the associatedchallenges

Overall we aimed to compare traditional (hallmark clinicalsymptoms basic biochemistry and muscle tissue investiga-tions) with a new method (exome sequencing and analysis ofa mitochondrial disease gene panel) to identify the mostuseful instrument for first-line assessment of patients with asuspected mitochondrial disease at initial presentation

MethodsThe primary research question addressed by this study wasthe identification of nongenetic (clinical radiologic andbiochemical) predictors of exome sequencing failing toidentify a genetically confirmed mitochondrial disorder(classification of evidence Class II)

Clinical Exome SequencingExtracted DNA was subject to library preparation using Agi-lent SureSelect XT (Agilent Technologies Santa Clara CA)and enrichment with a clinical exome bait set For samplestested before January 2019 the Agilent Focused ClinicalExome was used with added custom regions For samplestested from January 2019 the Agilent Custom ConstitutionalPanel was applied Enriched libraries were sequencing on anIllumina NextSeq500 instrument

Data were parsed through a bioinformatic pipeline developedin-house comprising alignment (Burrows-Wheeler Aligner)variant calling (freebayes) and variant annotation (Alamutbatch) Filtering was performed to remove common variants(at greater than 2 overall minor allele frequency in theExome Aggregation Consortium database) and commonfalse-positive calls

Variants passing filter were limited to target regions (Con-sensus Coding Sequence exons with 20 bp flanking intronicregions) of a virtual panel of genes The panel of genes usedfor analysis was iterated several times over the time course ofinvestigation to reflect changes in the PanelApp (panelappgenomicsenglandcouk) nuclear mitochondrial gene set and

GlossaryCOX = cytochrome c oxidase GOSHome = Great Ormond Street Hospital Clinical Exome ID = identifier MELAS =mitochondrial encephalopathy lactic acidosis and stroke-like episodes mtDNA = mitochondrial DNA RCEA = respiratorychain enzyme activity ROC = receiver operating characteristic

2 Neurology Genetics | Volume 7 Number 3 | June 2021 NeurologyorgNG

the coverage of the relevant genes in the 2 captures See tables e-1e-2 and e-3 (linkslwwcomNXGA427) for gene lists Patientwith identifiers (IDs) 1ndash14 were tested with the gene panel intable e-1 IDs 15ndash71 with the panel in table e-2 and IDs 72ndash85with the panel in table e-3 In addition to the nuclear mito-chondrial gene list several patients had additional phenotype-specific gene lists included in their clinical exome analysisreflecting the broad differential in their clinical diagnosis

Variants were classified according to the guidelines of theAmerican College of Medical Genetics and Genomics and theAssociation for Molecular Pathology18 with additional Asso-ciation for Clinical Genomic Science guidance Variantsdeemed to be clinically actionable (pathogeniclikely patho-genic variants in keeping with expected inheritance patternsand variants of uncertain clinical significance for which seg-regation studies could lead to reclassification as pathogeniclikely pathogenic) were confirmed by Sanger sequencing Thediagnosis of a genetic mitochondrial disease was made basedon the results of clinical exome sequencing (performed in allpatients) and mitochondrial DNA (mtDNA) studies (per-formed in 66 of patients) The cohort of patients was notfiltered or selected in any way after the clinical suspicion of amitochondrial disorder was raised

Clinical and Biochemical Data CollectionPatient information including phenotypic information neu-roimaging studies and routine biochemical test results wasextracted retrospectively from the electronic patient record atGreat Ormond Street Hospital London UK Specialized testswere performed to measure urine organic acids in urinesemiquantitatively as previously described19 and a range ofacylcarnitine species in dried blood spots in a quantitativemanner free carnitine acetyl carnitine (C2) propionyl car-nitine (C3) butyryl carnitine (C4) isovaleryl carnitine (C5)hexanoyl carnitine (C6) octanoyl carnitine (C8) tetradece-noyl carnitine (C141) and palmitoyl carnitine (C16)20

Muscle Histology StudiesLight and electron microscopy were performed as previouslydescribed21 Abnormal histologic findings included ragged redfibers and fibers staining negatively for cytochrome c oxidase(COX) Although nonspecific findings such as excess lipiddeposition increased variation in fiber size and abnormalmorphology of mitochondria on electron microscopy werealso classified as abnormal when they were present in largeamounts Mildly abnormal samples showed subtle changesincluding little excess lipid minimal variation in fiber size andmild atrophy

Figure 1 Patient Cohort Characterization

(A) Bar chart depicting number of patients inwhoma specific symptomwas found (B) Referral of patients for clinical exome sequencing permedical specialty(C) Pie chart depicting proportions of general neuroimaging outcomes (D) Summary of the outcome of respiratory chain enzyme activity (RCEA) mea-surements in muscle biopsy (E) General muscle (light and electron) histology results For all pie charts n values indicate in how many patients theinvestigation was performed

NeurologyorgNG Neurology Genetics | Volume 7 Number 3 | June 2021 3

Table 1 Biochemical and Genetic Details for Patients With Confirmed (n = 30) or Probable (n = 1) Diagnoses

Patientidentifier(ID) Sex

Age atpresentation Consanguinity

Elevatedmetabolites(Lac Ala Pro) Muscle studies (histology RCEA)

Mitochondrialdisease Clinical diagnosis Gene Allele 1 Allele 2

Patients with confirmed diagnosis

2 F 18 mo Unknown Normal Mildly abnormal histology decreasedcomplex IV activity

No Global developmental delay GRIN2A c3706_3709dupTGCGp(Asp1237ValfsTer12)

AD

3 M 8 mo Yes Lac Ala na Yes Mitochondrialleukodystrophy

IBA57 c802CgtTp(Arg268Cys)

c826CgtT p(Arg276Cys)

4 F 1 y Yes Lac Ala Pro Normal histology no RCEA defect Yes Complex multisystemmitochondrial disorder

FBXL4 c1304GgtAp(Arg435Gln)

Homozygous

5 M At birth No Normal Mildly abnormal histology no RCEAdefect

No Cohen syndrome VPS13B c6713TgtGp(Leu2238Ter)

Multiexon deletiona

6 M 14 mo Yes Lac Ala Pro na Yes Leigh syndrome LRPPRC c3900+1GgtT Homozygous

11 F 4 mo No Lac Mildly abnormal histology decreasedcomplex I and IV activities

Yes Mitochondrialcardiomyopathy

ELAC2 c1126_1127dupp(Val377GlnfsTer72)

c1283GgtA p(Arg428His)

17 M 5 mo No na Normal histology decreased complex Iand IV activities

Yes Complex multisystemmitochondrial disorder

FBXL4 c1703GgtCp(Gly568Ala)

Homozygous

24 M Antenatal(IUGR)

No Lac Mildly abnormal histology no RCEAdefect

Yes Complex multisystemmitochondrial disorder

FBXL4 c1288CgtTp(Arg430Ter)

c1750delTp(Cys584ValfsTer21)

25 F At birth No Lac No RCEA defect Yes Mitochondrial histiocytoidcardiomyopathy

NDUFB11 c183dupCp(Glu62ArgfsTer7)

Heterozygous (X-linked)

26 F 1 y No na Mildly abnormal histology decreasedcomplex II + III and IV activities

Yes Leigh syndrome SDHA c403GgtCp(Asp135His)

c1787AgtG p(Asp596Gly)

28 F 18 mo No Normal Mildly abnormal histology mildlydecreased complex I activity

Yes Mitochondrialcardiomyopathy

ELAC2 c2009delp(Cys670SerfsTer14)

c2245CgtT p(His749Tyr)

29 F At birth No Lac PAA na Mildly abnormal histology decreasedcomplex I activity

Yes Congenital lactic acidosis FOXRED1 c277CgtT p(Arg93Ter) c1261GgtA p(Val421Met)

31 F 8 mo No Normal Lac na Mildly abnormal histology loss ofcomplex I and IV activity

Yes Mitochondrialleukodystrophy withpremature ovarianinsufficiency

AARS2 c302GgtAp(Arg101His)

Homozygous

32 F 14 mo No Ala Pro na Yes Hyperammonemia CA5A Single exon deletion Homozygous

36 F 11 y 10 mo No Ala Pro na Yes Methylmalonic aciduria(vitamin B12 responsive)

MMAB c196GgtA p(Gly66Arg) c521CgtT p(Ser174Leu)

43 M At birth No Lac Ala Pro na Yes Mitochondrialleukodystrophy

EARS2 c184AgtT p(Ile62Phe) Homozygous

Continued

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Table 1 Biochemical and Genetic Details for Patients With Confirmed (n = 30) or Probable (n = 1) Diagnoses (continued)

Patientidentifier(ID) Sex

Age atpresentation Consanguinity

Elevatedmetabolites(Lac Ala Pro) Muscle studies (histology RCEA)

Mitochondrialdisease Clinical diagnosis Gene Allele 1 Allele 2

51 F 1 y No Ala na Yes Global developmental delaywith epilepsy

PDHA1 c1256_1259dupp(Trp421SerfsTer6)

Heterozygous (X-linked)

55 F At birth Yes Lac Ala Pro Normal histology RCEA na (delayedfreezing)

Yes Congenital lactic acidosis LRPPRC c3900+1GgtT Homozygous

62 F 18 mo Yes Normal na No Cerebellar atrophy EXOSC3 c238GgtT p(Val80Phe) Homozygous

64 M 6 mo No Normal Mildly abnormal histology decreasedcomplex IV activity

Yes Leigh syndrome C12orf65 c210delAp(Gly72AlafsTer13)

c258_270dupCATCCCCTCAGGCp(Ile91HisfsTer16)

66 F 18 mo No Normal Lac na na No Spinocerebellar ataxia CACNA1A c5006GgtAp(Arg1669Gln)

AD

77 M 7 mo No na Abnormal histology decreasedcomplex IV activity

Yes Mitochondrialcardiomyopathy

AARS2 c1774CgtTp(Arg592Trp)

Homozygous

78 F 5 mo Yes Lac Ala Pro na Yes Complex multisystemmitochondrial disorder

FBXL4 c1444CgtTp(Arg482Trp)

Homozygous

81 F 1 mo Yes na Abnormal histology decreasedcomplex I and IV activities

Yes Complex multisystemdisorder including SNHL andrenal failure

RMND1 c713AgtGp(Asn238Ser)

c1002+3AgtC

83 F 6 mo No Normal na No Congenital musculardystrophy

LAMA2 c3085CgtTp(Arg1029Ter)

Homozygous

Patient with probable diagnosis

75 M At birth No Lac Ala Mildly abnormal histology no RCEAdefect

Yes Leigh syndrome ECHS1 c748dupAp(Met250AsnfsTer8)

Heterozygousb

Patients with confirmed diagnosis (via alternative methods)

18 M 2 mo No Lac Ala Pro na Yes Leigh syndrome MT-ND1 m3955GgtAp(Ala217Thr)

mtDNA mutation (denovo)

22 F 9 mo No Normal Lac na na No Complexmovement disorderwith pontocerebellar atrophy

TBC1D24 c901CgtTp(Gln301Ter)

c605CgtT p(Ser202Leu)

34 F 15 mo No Normal Mildly abnormal histology decreasedcomplex I and IV activities

No Spastic ataxia 8 withhypomyelinatingleukodystrophy

NKX6-2 c121AgtT p(Lys41Ter) Homozygous

40 M At birth No Lac Ala Abnormal histology decreasedcomplex I activity andmildly decreasedcomplex IV activity

Yes Leigh syndrome MT-ND5 m13514AgtGp(Asp393Gly)

mtDNA mutation (denovo)

Continued

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Muscle Respiratory Enzyme Activity AssayFor assessment of RCEA muscle was snap-frozen on collec-tion and spectrophotometric assays of respiratory chaincomplexes I to IV were performed according to previouslyreported methods22

Statistical AnalysisStatistical testing and figure design were facilitated by R ver-sion 400 Continuous and discrete variables were correlatedwith the outcome of a positive mitochondrial diagnosis onexome sequencing by applying logistic regression Somevariables were transformed to log scale before the analysis toresemble normal distribution (figure e-1 a and b linkslwwcomNXGA427) To estimate effect size pseudo R2 wascalculated according to the McFadden method Receiveroperating characteristic (ROC) curves were drawn by ap-plying the R package plotROC (version 221) the correlo-gram by application of the ggcorrplot R package (version013) Significance levels of p values are indicated as followsthroughout the study p le 005 and p le 001

Standard Protocol Approvals Registrationsand Patient ConsentsVerbal consent was obtained from all patients (or their legalguardians) involved in the study This study was approved byan institutional committee and was registered as a clinicalaudit at Great Ormond Street Hospital NHS FoundationTrust (audit no 2381) All ethical institutional requirementshave been fulfilled and were followed during this retrospectivestudy

Data AvailabilityExome data cannot be supplied as they are patient specific Allnovel variants detected in the study will be made publiclyavailable on the ClinVar platform (ncbinlmnihgovclin-var)

ResultsClinical Patient Cohort CharacterizationThis is a retrospective review of 85 patients (44 females and41 males) with suspected mitochondrial disease who wererecruited consecutively for mitochondrial disease nucleargene panel analysis in the Great Ormond Street HospitalClinical Exome (GOSHome) from January 2015 to Novem-ber 2018 The overall median age at presentation was 050years (mean 192 SD 354) (figure e-2a linkslwwcomNXGA427) The most frequent clinical symptoms wereneurologic and included global developmental delay (n = 35)seizures (n = 14) hypotonia (n = 10) and encephalopathy (n= 9) cardiomyopathy (n = 10) was also a frequent finding(figure 1A) The patients were recruited for exome sequenc-ing from different pediatric disciplines in a tertiary clinicalsetting includingMetabolic Medicine (n = 57) Neurology (n= 25) Clinical Genetics (n = 2) and Respiratory (n = 1)(figure 1B) Seventy-four patients underwent neuroimagingby MRI which showed abnormal findings in 80 (n = 59) ofTa

ble

1Bioch

emical

andGen

eticDetailsforPatients

WithConfirmed

(n=30

)orProbab

le(n

=1)

Diagn

ose

s(con

tinue

d)

Patient

iden

tifier

(ID)

Sex

Age

at

pre

senta

tion

Consa

ngu

inity

Eleva

ted

meta

bolite

s(Lac

AlaP

ro)

Muscle

studies(histo

logy

RCEA

)Mitoch

ondrial

disease

Clinicald

iagn

osis

Gene

Allele

1Allele

2

49M

10y4mo

No

Ala

Mild

lyab

norm

alhistology

dec

reas

edco

mplexIa

ctivity

Yes

Leighsyndrome

MT-ND3

m101

97GgtA

p(A

la47

Thr)

mtD

NAmutationc

AbbreviationsAD=au

toso

mal

dominan

tAla

=alan

ine

IUGR=intrau

terinegrowth

retard

ationLac

=lactate

mtD

NA=mitoch

ondrial

DNAn

a=nota

vaila

bleP

AA=plasm

aam

inoac

idP

ro=prolin

eRCEA

=resp

iratory

chain

enzymeac

tivity

Thistableincludes

allp

atients

oftheco

hortw

horece

ived

age

neticdiagn

osis(diagn

ose

dviamitoch

ondrialpan

eltestingaltern

ativepan

eltestingorother

methodsfordetailssee

sectionldquoM

itoch

ondrial

Disea

seGen

esrdquo)For

alld

isord

erstheinheritan

cepattern

asper

previouspublicationswas

autoso

mal

rece

ssive

exce

ptforthefollo

wingpatientsID25

andID

51(both

X-lin

ked)ID

2an

dID

66(rep

orted

asADdisord

ers)H

omozygo

usmutations

areindicated

byaco

mmen

tin

theco

lumnofthese

condalleleF

ivepatients

werediagn

ose

dusingother

methods(ID

22w

hole-gen

omese

quen

cing

ID34

whole-exo

mese

quen

cing

IDs18

40

and49

mtD

NAse

quen

cean

alysis)Gen

enam

esareac

cord

ingto

HUGOGen

eNomen

clature

Committeenomen

clatureF

ordetailedva

rian

tdes

criptiona

sses

smen

tofp

athoge

nicityan

dnove

ltyofg

eneticva

rian

tssee

table

e-7(linkslw

wcomN

XG

A42

7)

aMultiexo

ndeletionwas

detec

tedbyread

dep

than

alysis

usingEx

omeD

epth

(see

Methods)

andwas

confirm

edusingquan

titative

PCR

bDeficiency

ofEC

HS1

confirmed

byen

zymeac

tivity

studies

cMaternal

sample

nottested

6 Neurology Genetics | Volume 7 Number 3 | June 2021 NeurologyorgNG

patients (figure 1C) In 53 patients (62 of all patients)muscle tissue was biopsied and investigated (skeletal muscle n= 52 cardiac muscle n = 1) of which 48 (5 not assayed due todelayed freezing) were tested for mitochondrial RCEAnamely complex I II + III (assessed together) and IV In-dividual patients either showed single or combined RCEA

deficiencies specifically isolated loss of complex I (n = 4)combined loss of complex I and complex IV (n = 12) com-bined loss complexes II + III and IV (n = 1) isolated loss ofcomplex IV activity (n = 17) or no evidence of a mitochon-drial RCEA deficiency (n = 14) (figure 1D table e-4) Fur-thermore in 48 of the patients who underwent muscle biopsy

Figure 2 Biochemical Characterization

(A) Boxplots of CSF and plasma biomarkers Dashed horizontal lines indicate reference ranges for CSF lactate and plasma lactate normal values are below thedashed horizontal line (B) Violin plots illustrating results of semiquantitative urine organic acid measurements points represent mean values (C) Horizontalboxplots of acylcarnitine results Boxplots consist of horizontalmarks for the 25th percentile themedian and the 75th percentile whiskers extend to the 5th and95th percentile and outliers are represented as separate individual values (D) Boxplot of levels of respiratory chain enzyme activities normalized to citratesynthase (CS) activity Dashed horizontal lines indicate reference ranges All plots are split in 2 groups of patients with amitochondrial diagnosis in red and thosewith no mitochondrial diagnosis in gray Significance of differences was determined by logistic regression analysis = p le 005 = p le 001

NeurologyorgNG Neurology Genetics | Volume 7 Number 3 | June 2021 7

histology investigations were performed and revealed normal(n = 5) mildly abnormal (n = 29) and abnormal (n = 14)findings (figure 1E)

Mitochondrial Disease GenesMolecular genetic analysis of patient samples was performedusing a clinical exome panel Genes encoded by mtDNA wereinvestigated by other means (screening for common pointmutations and large-scale rearrangements andor completemitochondrial genome sequencing and mtDNA quantifica-tion) in 56 cases (66 of all patients) The 85 patients werereferred for clinical exome sequencing at a median age of 592years (mean 671 SD 509) (figure e-2a linkslwwcomNXGA427) which represents a considerable delay aftertheir initial clinical presentation (time of delay median 367years mean 479 range 0ndash1650 years) (figure e-2b) Thetime from clinical presentation to completed clinical exomesequencing was a median of 416 years showing a high vari-ability (range 033ndash1708 years) (figure e-2 b and c) Thismight have been partly attributable to a lack of clinical(ie nonresearch) diagnostic genome-wide genetic testing

before the development and implementation of the GOSH-ome The median time from request to report was 196 dayswith some cases resolved within just over a month and othersthat took more than 1 year (range 48ndash418 days) (figure e-2b)The variance in reporting time can be explained by clinicalurgency with some cases prioritized to assist clinical man-agement or reproductive options and case complexity pa-tients in whom complex variants were identified that requiredadditional validation assays took longer to reach reportingstatus

Twenty-five of the 85 patients received a confirmed geneticdiagnosis via the clinical exome panel with the following af-fected genes FBXL4 (n = 4) AARS2 (n = 2) ELAC2 (n = 2)LRPPRC (n = 2) C12orf65 CA5A CACNA1A EARS2EXOSC3 FOXRED1 GRIN2A IBA57 LAMA2 MMABNDUFB11 PDHA1 RMND1 SDHA and VPS13B (all n = 1underlined genes are not considered mitochondrial diseasegenes and were identified via additional panel analysis) (table1) One additional patient received a probable diagnosis withonly 1 heterozygous mutation found in ECHS1 Although we

Figure 3 Predictive Parameters for Mitochondrial Disease

The panels in this figure describe comparisons between patients with a mitochondrial diagnosis (red) and patients with no diagnosis (including non-mitochondrial diagnosis gray) (A) Age at presentation of individual patients for better visibility on the log scale (y-axis) patients with antenatal abnormalitieswere assigned an age at onset of 01 day and for onset at birth of 1 day (B) Bar chart illustrating the occurrence of themost frequent symptoms in the cohortincluding diagnostic rate in percent for each individual symptom above the bars as calculated by number of patients with this symptom and amitochondrialdiagnosis divided by the number of all patients with this symptom (C) Heatmap depicting levels of positive predictive value (PPV) negative predicate value(NPV) sensitivity and specificity for different test modalities calculated using a genetic mitochondrial diagnosis as the gold standard In the calculations apositive outcome of test modalities was considered as follows raised levels of lactate alanine and proline decreased activity of RCEA complexes andabnormal neuroimaging RCEA or histology (D) ROC curves for selected continuous test variables (E) Bar graph depicting the outcome of clinical exomeanalysis per referring specialty AUC = area under the ROC curve RCEA = respiratory chain enzyme activity ROC = receiver operating characteristic

8 Neurology Genetics | Volume 7 Number 3 | June 2021 NeurologyorgNG

have not identified a second ECHS1 variant in this patientenzymatic studies confirmed a deficiency of enoyl-CoAhydratase (ECHS1) (patient ID 75) Of note some of theidentified nuclear genes encode mitochondrial proteins butare not considered to cause a classical mitochondrial condi-tion and were identified via alternative panels as part of theclinical exome sequencing analysis (CA5A in patient ID 32MMAB in patient ID 36) In addition 5 patients were di-agnosed via alternative analyses Three patients were di-agnosed with mtDNA mutations by direct mitochondrialgenome sequencing because the clinical exome sequenceanalysis pipeline applied in this study was unable to detectmtDNA mutations Two cases had known pathogenicmtDNA variants m13514AgtG p(Asp393Gly) in MT-ND5(patient ID 40) and m10197GgtA p(Ala47Thr) inMT-ND3(patient ID 49) For the third patient we report a novelpathogenic variant m3955GgtA p(Ala217Thr) in MT-ND1as a new cause of Leigh syndrome in a boy who presented at 2months with an early infantile epileptic encephalopathy lacticacidosis and brain MRI demonstrating bilateral symmetricalsignal abnormality involving the caudate nuclei putaminamidbrain medulla upper cervical cord and perirolandiccortex The variant was heteroplasmic with 89 mutationload in blood DNA from the affected infant but was absent inbloodDNA from his unaffectedmother The variant has never

previously been reported and is absent in MitoWheel andMITOMAP (mitowheelorg mitomaporg both accessed onOctober 17 2020) Previously reported pathogenic variants inMT-ND1 includem3376GgtA p(Glu24Lys) reported to cause aLeber hereditary optic neuropathymitochondrial encephalopa-thy lactic acidosis and stroke-like episodes (MELAS) overlapsyndrome and m3697GgtAp(Gly131Ser) associated withMELAS and Leigh syndromes In 2 cases a diagnosis wasestablished bywhole-exome sequencing patient ID 22was foundto be compound heterozygous for 2 mutations in TBC1D24c901CgtT p(Gln301Ter) and c605CgtT p(Ser202Leu) andpatient ID 34 carried the homozygous pathogenic mutationc121AgtT p(Lys41Ter) in NKX6-2 (table 1) The global di-agnostic rate in our study was 365 Overall 24 patients wereidentified with a genetically confirmedmitochondrial disease andwe are reporting a total of 20 novel disease-causing variants (table1) Seven patients were diagnosed with a nonmitochondrialdisorder (table 1)

Biochemical PhenotypingThe patients had undergone a variety of different test mo-dalities before genetic sequencing (figure e-3a linkslwwcomNXGA427) Routine biochemical investigationsrevealed various abnormalities including elevated lactate inCSF (n = 9 as assessed in 36 patients ie in 25 in whom the

Figure 4 Odds Ratios of Predictive Parameters

Forest plot depicting effect sizes of diagnosticmeasures including 95 confidence interval (CI)derived from logistic regression analysis (A) Thesecontinuous variables were log transformed beforeanalysis (B) These variables are all discrete egpresence or absence of cardiomyopathy andpresence or absence of elevated lactate R2 = R2

according to the McFadden method

NeurologyorgNG Neurology Genetics | Volume 7 Number 3 | June 2021 9

test was performed) and plasma (n = 23 as assessed in 68patients ie in 34) elevated plasma alanine (n = 26 asassessed in 75 patients ie in 35) and plasma proline (n =15 as assessed in 75 patients ie in 20) (figure e-3b) All 4tests were able to distinguish between patients with mito-chondrial disease and patients without a diagnosis of a mi-tochondrial disorder (figure 2A) Consistent with raised CSFand plasma lactate levels semiquantitative urine organic acidanalysis revealed elevated levels of urine lactate and pyruvatein the mitochondrial patient group (figure 2B) In additionseveral metabolites of the Krebs cycle were also significantlyelevated such as fumarate 2-oxoglutarate and citrate (figure2B) Quantification of acylcarnitine species showed a signifi-cant elevation of butyryl carnitine (figure 2C) Surprisinglyquantitative RCEA measurements showed no correlationwith the presence of a confirmed mitochondrial disease di-agnosis (figure 2D)

Predictive Parameters ofMitochondrial DiseaseTo identify predictive factors for the presence of a mito-chondrial disorder we investigated the correlation of clinicalsymptoms and investigation findings with a positive mito-chondrial disease genetic diagnostic outcome as obtained in24 patients Age at presentation did not correlate with a ge-netic diagnosis of mitochondrial disease (figure 3A) Of thewide range of clinical symptoms found in the cohort mostsingle symptoms were not strongly correlated with a positivediagnosis (figure 3B) The highest diagnostic rates were notedfor cardiomyopathy (60) visual impairment (62) andrenal tubulopathy (67 only in n = 3 patients) whereas the 2former symptoms were the only clinical symptoms signifi-cantly associated with a mitochondrial disease diagnosis(figure 3B) Of interest a third (34) of all patients with thenonspecific symptom of global developmental delay receiveda positive diagnosis (figure 3B) Other prevalent symptoms inthis cohort were not predictive of a positive genetic diagnosis

As the clinical assessment does not seem to be able to stratifybetween patients with mitochondrial disease and patientswithout mitochondrial disease in our cohort additional testmodalities were evaluated regarding their ability to predictmitochondrial disease (figure 3C) Elevatedmetabolites in CSFand plasma (lactate alanine proline) were consistently asso-ciated with a higher positive predictive value (50ndash67)compared with other tests (figure 3C) The same test modal-ities together with neuroimaging proved even more useful withregard to a high negative predictive value which would allowexclusion of a mitochondrial disorder in the case of normalresults in 80ndash89 of cases (figure 3C) Elevated biomarkers(at least 1 out of lactate alanine or proline) showed an un-expectedly high specificity in our patient cohort ranging from76 to 89 (figure 3C) As expected from a biological per-spective these biomarkers correlated positively with each other(figure e-4 linkslwwcomNXGA427) Of interest althoughwe observed a linear relationship between plasma lactate andthe other 2 plasma metabolites in nonmitochondrial patients

the levels of alanine and proline were independent of lactate inmitochondrial disease patients (figure e-5) These biomarkersalso perform well in terms of sensitivity (except for proline)Abnormal RCEA and abnormal muscle histology are similarlysensitive parameters (figure 3C) Although muscle testsshowed a reasonable sensitivity neuroimaging was the mostsensitive test modality (90) (figure 3C) When it comes topositive predictive value and specificity RCEA testing andhistology investigations performed poorly abnormal RCEAonly showed a positive predictive value of 32 (1134) andabnormal muscle histology of 28 (1243) (figures 3C ande-3b) Ragged red fibers and COX-negative fibers were specificfor mitochondrial disease as expected but had low sensitivitybeing detected in only 1 patient each (patient IDs 40 and 81respectively) both of whom were diagnosed with a geneticallyconfirmed mitochondrial disease (pathogenic variants in MT-ND5 and RMND1 respectively) Other samples with a con-firmed gene defect affectingmitochondrial translation (AARS2C12orf65 EARS2 ELAC2 and LRPPRC) did not show any ofthese 2 mitochondrial hallmark histology findings Additionalhistology findings such as excess lipids variation in fiber sizeand type or abnormal mitochondrial morphology did notcorrelate with a positive mitochondrial diagnosis (table e-5)

Further evaluation of diagnostic test modalities by ROC curveanalysis revealed that CSF lactate is the best continuous vari-able in the data set to distinguish between a patient with mi-tochondrial disease vs a nonmitochondrial disease state with anarea under the ROC curve of 091 (figure 3D) The afore-mentioned simple plasmametabolite tests (lactate alanine andproline) performed reasonably and again better than the moresophisticated studies of RCEA in muscle tissue (figure 3D)Other continuous parameters such as plasma arginine or age atpresentation were not able to predict mitochondrial disease inthe study cohort (figure e-6 linkslwwcomNXGA427)

Of the referring specialties only Neurology and MetabolicMedicine provided a large number of patient samples thelatter showed a significantly higher rate of positive mito-chondrial diagnoses (35) compared with the former (12)(figure 3E) which may reflect the types of patients referred toeach of these specialties

To quantify the effect size of each test modality we performedlogistic regression analysis and calculated odds ratios for eachcontinuous variable in the data set (tables e-5 and e-6 linkslwwcomNXGA427) Depending on their distributionspecific continuous variables were log transformed before theanalysis (figure e-1) In line with the previous statisticalanalysis CSF lactate is a strong predictor of mitochondrialdisease and increases the odds of a mitochondrial diagnosis by16 times in case of an elevation above the reference range(figure 4 A and B) Previously mentioned tests such as otherlactate associated parameters as well as Krebs cycle metabo-lites showed a significantly raised odds ratio (figure 4 A andB) Of interest only bilateral basal ganglia abnormalities wereassociated with a mitochondrial disease diagnosis in our study

10 Neurology Genetics | Volume 7 Number 3 | June 2021 NeurologyorgNG

cohort whereas other neuroimaging findings including cere-bellar hypoplasia cerebral atrophy and white matter abnor-malities were not (figure 4B table e-5)

Mitochondrial Disease ScoreThe suspicion of a mitochondrial disorder for each patient inthis study was not based on a systematic assessment Theclinical exome investigation was initiated based on the in-dividual clinicianrsquos judgment We have retrospectively applieda mitochondrial disease score developed in this study whichwas based on a previous mitochondrial disease score23 Thepresence of one of the 10 most prevalent symptoms in theoverall cohort (figure 1A) scored 1 point each (maximumclinical subscore of 10 points) whereas abnormal neuro-imaging biochemistry (lactate alanine proline and RCEA 1point each) and muscle histology scored 1 point each(maximum investigation subscore of 6 points) representingclinical symptoms as well as biochemicalimaging aberrationsWhen the score was applied to the patient cohort of this studyit ranged from 0 to 9 (figure e-7a linkslwwcomNXGA427) and the mean overall score of the 85 patients was 364(SD 185) (figure e-7b) The overall score and the in-vestigation subscore were significantly associated with apositive mitochondrial diagnosis (figures 4B and e-7b) and atotal score gt4 points should trigger genetic follow-up inves-tigations in a patient with suspected mitochondrial disease

DiscussionIn this study we used clinical exome sequencing to search for agenetic diagnosis in patients with clinically suspected mitochon-drial disease and compared the results with traditional markers Agenetic diagnostic confirmation was established in over a third ofall cases For the remaining patients the question remains as towhether they had a mitochondrial disorder at all or whether theirphenotype only mimicked this group of conditions4

The limited diagnostic rate can be partly explained by themethod of exome sequencing applied in this study whichmight have missed some of the disease-causing variants due toseveral limitations including (1) limited number of genes inthe clinical panel (2) analysis of mtDNA in only 66 ofpatients (3) potential for insufficient coverage of certain re-gions (4) test sensitivity for certain variant typesmdashcopynumber testing was performed as standard using Exome-Depth but the sensitivity is unknown and the sensitivity todetect insertiondeletion variants using short read sequencingis also known to be lowwhen compared with single nucleotidevariants and (5) causative variants lying outside the targetregion (eg promoter untranslated regions and deepintronic variants) Addressing the above points in the un-diagnosed participants of our study might yield more di-agnoses of mitochondrial disease although generallyspeaking mtDNA analysis was not performed in those pa-tients deemed to have a lower suspicion of mitochondrialdisease Although there are some drawbacks of the methodapplied in this study the application of a panel-based clinical

exome sequencing method also has some clear advantagescompared with whole-exome or genome approaches eg thenumber of variants of unknown significance is lower becauseonly a subset of genes is specifically analyzed Some variantsespecially if previously published in relation to a distinct dis-ease phenotype are classified as pathogenic but the remain-ing variants are often difficult to interpret Therefore weemphasize that clinical exome sequencing should never beused as an isolated method but always accompanied by a setof follow-up procedures including segregation studies in thefamily complementary DNA sequencing if indicated andmost importantly functional testing where necessary (eg asin patient ID 75 in this study)

When comparing the outcome of the clinical exome analysisin our study with predictive parameters our study demon-strates that single clinical symptoms or the application of aclinical score are overall poor predictors of mitochondrialdisease as previously discussed4 However the combinationof suspicious clinical features with the results of noninvasivemethods such as neuroimaging (excellent sensitivity) andbiomarkers (in CSF blood and urine) such as lactate pyru-vate and alanine (high specificity) can significantly improvethe pretest probability of a mitochondrial disorder Thesebasic investigations should therefore be completed beforeclinical exome sequencing is initiated depending on theclinical urgency potentially together with other promisingbiomarkers currently being established in the field such asFGF21 and GDF1524 Similar strategies are described incurrent guidelines for diagnosis and management of mito-chondrial disorders623 and comparable rates of sensitivityand specificity for biomarkers have been described2526

Furthermore we have compared the results of muscle in-vestigations performed in the majority of our patients with theoutcome of the clinical exome analysis Previous exomestudies for mitochondrial disease have not performed such adirect comparison of exome and muscle investigations Thusour parallel clinical exome and muscle data set will provide animportant historical resource going forward as fewer musclebiopsies are performed for mitochondrial disease worldwideOur data reveal that the traditional muscle techniques have apoor diagnostic specificity and it could be argued that musclebiopsies should be avoided in the future as a first-line test andinstead clinical exome analysis should be performed as apriority when the suspicion of a mitochondrial disorder hasbeen raised during the initial clinical and biochemical as-sessment of the patient Even in clinically urgent situationssuch as the neonatalpediatric intensive care unit next-generation sequencing methods might yield an earlier resultthan investigation of muscle tissue as shown for Pearsonsyndrome and other conditions2728 Our study shows thatmuscle histology was completely normal in only 10 of allcases which were analyzed with this technique The in-sufficient specificity was further underlined by the result ofmore than 60 of cases with slightly abnormal histologyprecluding a definite diagnosis based on muscle histology

NeurologyorgNG Neurology Genetics | Volume 7 Number 3 | June 2021 11

Furthermore RCEA measurements in muscle show a lowpositive predictive value and were not specific enough to re-liably diagnose mitochondrial disease These conclusions arelimited by the fact that not all patients in this cohort wereinvestigated by mtDNA analysis

On the basis of these results we suggest that analyses relying onmuscle biopsy material should be replaced by clinical exomesequencing in the initial stages of the mitochondrial diagnosticworkflow Muscle biopsy still has a role in the evaluation ofsuspected mitochondrial disease and should be considered inthe following 3 scenarios (1) critical illness (2) for confir-mation of pathogenicity of variants of unknown significanceidentified by exome or genome sequencing and (3) if geneticinvestigations do not yield any positive findings and a strongclinical suspicion of mitochondrial disorder remains

Finally the initial contact between the physician and the pa-tient will remain the crucial key step in finding a diagnosis forpatients affected by a mitochondrial disease and there is nosubstitute for thorough history taking and physical examina-tion2 Our study illustrates that numerous patients go througha years-long diagnostic odyssey We can only speculate on thereasons for the diagnostic delay illuminated by our data (1)access to diagnostic methods the clinical exome analysisdeveloped in this study could have presented the first op-portunity to the referring physician to actually perform awider genetic analysis and (2) uncertainty of clinical courseour study shows that in younger patients the diagnostic delayis particularly long possibly reflecting a wait-and-see ap-proach in younger children with potentially nonspecific clin-ical signs We expect that costs for exome studies will continueto fall29 and turnaround times will further improve enablingearly recruitment of patients for exome or genome-widestudies and consequently shortening the diagnostic odysseyfor patients with suspected mitochondrial disease

AcknowledgmentThe authors acknowledge the clinicians who referred thepatients for diagnostic purposes into the GOSHome studyThey also thank Helen Aitkenhead for her help withbiochemical data retrieval

Study FundingAll investigations were performed as part of routine clinicalcare S Rahman acknowledges grant funding from the GreatOrmond Street Hospital Childrenrsquos Charity the NIHR GreatOrmond Street Hospital Biomedical Research Centre andthe Lily Foundation TSJ receives funding from GreatOrmond Street Childrenrsquos Charity The Brain TumourCharity Children with Cancer UK Cancer Research UKNIHR and the Olivia Hodson Cancer Fund

DisclosureThe authors of the manuscript declare no conflict of interestThere is no commercial association that might pose or createthe appearance of a conflict of interest with the information

presented in the submittedmanuscript Go toNeurologyorgNG for full disclosures

Publication HistoryReceived by Neurology Genetics February 12 2021 Accepted in finalform April 6 2021

Appendix Authors

Name Location Contribution

PatrickForny MDPhD

UCL Great Ormond StreetInstitute of Child HealthUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent major role in theacquisition of data studyconcept or design andanalysis or interpretation ofdata

EmmaFootitt PhD

Great Ormond StreetHospital for ChildrenNHS FoundationTrust London UnitedKingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

James EDavisonPhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

AmandaLam PhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

Cathy EWoodwardBSc

National Hospital forNeurology andNeurosurgery LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

SpyrosBatzios MDPhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

SanjayBhate MD

Great Ormond StreetHospital for ChildrenNHS Foundation TrustLondon UnitedKingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

AnupamChakrapaniMD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

MaureenCleary MDFRCP

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

Paul GissenPhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

StephanieGrunewaldFRCP PhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

Jane AHurst FRCP

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

12 Neurology Genetics | Volume 7 Number 3 | June 2021 NeurologyorgNG

References1 Rahman J Rahman S Mitochondrial medicine in the omics era Lancet 2018391

2560ndash25742 Rahman S Mitochondrial disease in children J Intern Med 2020287609ndash6333 Boenzi S Diodato D Biomarkers for mitochondrial energy metabolism diseases

Essays Biochem 201862443ndash4544 Parikh S Karaa A Goldstein A et al Diagnosis of lsquopossiblersquomitochondrial disease an

existential crisis J Med Genet 201956123ndash1305 Debray F-G Mitchell GA Allard P Robinson BH Hanley JA Lambert M Diagnostic

accuracy of blood lactate-to-pyruvate molar ratio in the differential diagnosis ofcongenital lactic acidosis Clin Chem 200753916ndash921

6 Parikh S Goldstein A Koenig MK et al Diagnosis and management of mitochondrialdisease a consensus statement from the Mitochondrial Medicine Society Genet Med201517689ndash701

7 Haas RH Parikh S Falk MJ et al The in-depth evaluation of suspected mitochondrialdisease Mol Genet Metab 20089416ndash37

8 Kowaloff EM Phang JM Granger AS Downing SJ Regulation of proline oxidaseactivity by lactate Proc Natl Acad Sci USA 1977745368ndash5371

9 Kuhl I Miranda M Atanassov I et al Transcriptomic and proteomic landscape ofmitochondrial dysfunction reveals secondary coenzyme Q deficiency in mammalsElife 20176e30952

10 Clark JB Hayes DJ Byrne E Morgan-Hughes JA Mitochondrial myopathies defects inmitochondrial metabolism in human skeletal muscle Biochem Soc Trans 198311626ndash627

11 Walker UA Collins S Byrne E Respiratory chain encephalomyopathies a diagnosticclassification Eur Neurol 199636260ndash267

12 Bernier FP Boneh A Dennett X Chow CW Cleary MA Thorburn DR Diagnosticcriteria for respiratory chain disorders in adults and children Neurology 2002591406ndash1411

13 McFarland R Taylor RW Turnbull DM A neurological perspective onmitochondrialdisease Lancet Neurol 20109829ndash840

14 Hui J Kirby DM Thorburn DR Boneh A Decreased activities of mitochondrialrespiratory chain complexes in non-mitochondrial respiratory chain diseasesDevMedChild Neurol 200648132ndash136

15 Wortmann SB Koolen DA Smeitink JA van den Heuvel L Rodenburg RJ Wholeexome sequencing of suspected mitochondrial patients in clinical practice J InheritMetab Dis 201538437ndash443

16 Theunissen TEJ NguyenM Kamps R et al Whole exome sequencing is the preferredstrategy to identify the genetic defect in patients with a probable or possible mito-chondrial cause Front Genet 20189400

17 Genomics England PanelApp [online] Available at panelappgenomicsenglandcouk Accessed October 19 2019

18 Richards S Aziz N Bale S et al Standards and guidelines for the interpretation ofsequence variants a joint consensus recommendation of the American College ofMedical Genetics and Genomics and the Association for Molecular Pathology GenetMed 201517405ndash424

19 Chalmers RA Organic Acids in Man Analytical Chemistry Biochemistry and Diagnosisof the Organic Acidurias Springer Netherlands 1982

20 Millington DS Kodo N Norwood DL Roe CR Tandem mass spectrometry a newmethod for acylcarnitine profiling with potential for neonatal screening for inbornerrors of metabolism J Inherit Metab Dis 199013321ndash324

21 Rahman S Lake BD Taanman JW et al Cytochrome oxidase immunohistochem-istry clues for genetic mechanisms Brain 2000123(pt 3)591ndash600

22 Hargreaves P Rahman S Guthrie P et al Diagnostic value of succinate ubiquinonereductase activity in the identification of patients with mitochondrial DNA depletionJ Inherit Metab Dis 2002257ndash16

23 Witters P Saada A Honzik T et al Revisiting mitochondrial diagnostic criteria in thenew era of genomics Genet Med 201820444ndash451

24 Lehtonen JM Auranen M Darin N et al Diagnostic value of serum biomarkersFGF21 and GDF15 compared to muscle sample in mitochondrial disease J InheritMetab Dis 202144469ndash480

25 Davis RL Liang C Edema-Hildebrand F Riley C Needham M Sue CM Fibroblastgrowth factor 21 is a sensitive biomarker of mitochondrial disease Neurology 2013811819ndash1826

26 Tarnopolsky M Stevens L MacDonald JR et al Diagnostic utility of a modifiedforearm ischemic exercise test and technical issues relevant to exercise testingMuscleNerve 200327359ndash366

27 Akesson LS Eggers S Love CJ et al Early diagnosis of Pearson syndrome in neonatalintensive care following rapid mitochondrial genome sequencing in tandem withexome sequencing Eur J Hum Genet 2019271821ndash1826

28 Mestek-Boukhibar L Clement E Jones WD et al Rapid Paediatric Sequencing(RaPS) comprehensive real-life workflow for rapid diagnosis of critically ill childrenJ Med Genet 201855721ndash728

29 Schwarze K Buchanan J Taylor JC Wordsworth S Are whole-exome and whole-genome sequencing approaches cost-effective A systematic review of the literatureGenet Med 2018201122ndash1130

Appendix (continued)

Name Location Contribution

RichardScott PhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

SimonHeales PhD

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

Thomas SJacquesFCPath

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent

ThomasCullupFRCPath

Great Ormond StreetHospital for Children NHSFoundation Trust LondonUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent major role in theacquisition of data andstudy concept or design

ShamimaRahmanFRCP PhD

UCL Great Ormond StreetInstitute of Child HealthUnited Kingdom

Draftingrevision of themanuscript for contentincluding medical writing forcontent major role in theacquisition of data studyconcept or design andanalysis or interpretation ofdata

NeurologyorgNG Neurology Genetics | Volume 7 Number 3 | June 2021 13

DOI 101212NXG000000000000059720217 Neurol Genet

Patrick Forny Emma Footitt James E Davison et al Diagnosing Mitochondrial Disorders Remains Challenging in the Omics Era

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